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San Francisco Bay Area

Neha Boloor

Machine Learning Engineer & Artist

I am a Machine Learning Engineer currently building Generative AI based solutions for validation and verification of autonomous driving vehicles at Zoox.

Jun 2024 - Present

Machine Learning Engineer @ Zoox

Developing machine learning models to generate realistic and diverse synthetic scenarios for testing autonomous vehicles.

Feb 2023 - Jun 2024

Research Engineer @ Matic Robots

Developed an autonomous exploration algorithm enabling fast and intelligent mapping of new homes.

Aug 2021 - Dec 2022

Master's in Computer Vision @ Carnegie Mellon University

Focused on deep learning for computer vision, with research projects in 3D perception and smart city infrastructure.

JN Tata Scholar 2021

Jun 2018 - Jul 2021

Senior Software Engineer @ Oracle

Designed and developed key marketing segmentation, data integration, and performance enhancement features for Oracle Marketing Cloud's SaaS products.

Aug - Dec 2017

Research Intern @ IIT Madras

Worked on content-based image retrieval using deep learning at the Computer Vision Lab, under Prof. Anurag Mittal

May - Aug 2017

Summer Analyst @ Goldman Sachs

Implemented an AI-based search tool for ticket resolution.

Aug 2014 - May 2018

Bachelor's in Information Technology @ National Institute of Technology Karnataka

Awarded Best Outgoing Student and graduated with distinction.

Awards & Recognition

  • 🏆 GOLD GLOBEE AWARDS WINNER - Women of the Year Technology category (2025)
  • 🏆 GOLD TITAN INNOVATION AWARDS WINNER - Innovation in Technology - Best Artificial Intelligence Technology Innovation (2025)
  • 🎤 Keynote Speaker - IEEE ICSCIS 2025, presenting "Vision Zero: Leveraging AI and Advanced Datasets for Safer, Smarter Roadways in Smart Cities"
  • 📚 Workshop Paper Accepted - "Linear Memory SE(2) Invariant Attention" at RSS 2025 Workshop on Equivariant Systems: Theory and Applications in State Estimation, Artificial Intelligence and Control (Ethan Pronovost, Neha Boloor, Noureldin Hendy, Peter Schleede, Andres Morales, Nicholas Roy)
  • 📊 Lead Author - USDOT-backed ROADWork Dataset (archived in ROSA P, TRID, and arXiv)
  • 📝 Profiled by MSN - Featured in a MSN dedicated article highlighting my work and impact in AI.